A compensation quantity acquisition device acquires vibration of the movement target in a second axis direction, orthogonal to the first axis direction when the movement target is moved in the first axis direction, acquires a positional frequency characteristic by performing Fourier transformation on the acquired vibration in the second axis direction, performs inverse Fourier transformation on the positional frequency characteristic from which the component of position independent frequency in the second axis direction (that occurs independently of a position of the movement target in the first axis direction) has been removed, to recover the vibration of the movement target in the second axial direction as position dependent vibration, and acquires positional compensation quantity of the movement target in the second axis direction that cancels the position dependent vibration.

A computing system detects an event. (A) A frequency spectrum is computed using a Fourier transform. (B) (A) is repeated a predefined plurality of times with successive windows of observation vectors. Each window of the successive windows includes a subset of the observation vectors. The successive windows include successive subsets selected sequentially in time. (C) An average frequency spectrum is computed from the frequency spectrum computed the predefined plurality of times. (D) A plurality of segmented average frequency spectra is computed from the computed average frequency spectrum. Each segmented average frequency spectrum of the plurality of segmented average frequency spectra is computed for a frequency band of a plurality of predefined frequency bands. (E) When an event has occurred is determined based on the computed plurality of segmented average frequency spectra and a predefined threshold value.

The present disclosure is directed toward a diagnostic method for a spindle arm of a machine. The method includes rotating the spindle arm of the machine at a first rotational speed, and acquiring, from an accelerometer, data indicative of a vibrational response of the spindle arm operating at the first rotational speed. The accelerometer is disposed along the spindle arm. The method further includes converting the vibrational response to a frequency based response to obtain a first frequency response, determining whether an amplitude of the first frequency response exceeds a diagnostic threshold, and performing a designated correction on the machine in response to the frequency response exceeding the diagnostic threshold.

A frequency spectrum is computed using a Fourier transform a predefined plurality of times with successive windows of observation vectors, wherein each window of the successive windows includes a subset of observation vectors, wherein the successive windows include successive subsets selected sequentially in time. An average frequency spectrum is computed. A plurality of segmented average frequency spectra is computed, wherein each segmented average frequency spectrum is computed for a frequency band of predefined frequency bands. A distance value is computed using a trained support vector data description model with the segmented average frequency spectra. When an event has occurred is determined based on a comparison between the distance value and a predefined threshold. A vector is computed from the segmented average frequency spectra using t-stochastic neighbor embedding. When an event has occurred based on the comparison, an event indicator is presented on a graph using the vector.

A computing system detects an event. (A) A frequency spectrum of observation vectors is computed using a Fourier transform. Each observation vector includes a sensor value. (B) (A) is repeated a predefined plurality of times with successive windows of the observation vectors. Each window of the successive windows includes a subset of the observation vectors. The successive windows include successive subsets selected sequentially in time. (C) An average frequency spectrum is computed from the frequency spectrum computed the predefined plurality of times. (D) A predefined noise filter is applied to the average frequency spectrum to define a filtered frequency spectrum. (E) A distance value is computed between the filtered frequency spectrum and a predefined reference spectrum using a distance computation function. (F) When an event has occurred is determined based on a comparison between the computed distance value and a predefined distance threshold.

A failure prediction method of predicting a failure of a component of a robot including a robot arm having the component and a detection section that detects information on vibration characteristics when the robot arm moves, includes generating a failure prediction model for prediction of the failure of the component by machine learning based on the information on vibration characteristics, and predicting the failure of the component based on an estimated value of failure prediction output by the generated failure prediction model when the information on vibration characteristics is input to the generated failure prediction model.

The present disclosure is directed toward a diagnostic method for a spindle arm of a machine. The method includes rotating the spindle arm of the machine at a first rotational speed, and acquiring, from an accelerometer, data indicative of a vibrational response of the spindle arm operating at the first rotational speed. The accelerometer is disposed along the spindle arm. The method further includes converting the vibrational response to a frequency based response to obtain a first frequency response, determining whether an amplitude of the first frequency response exceeds a diagnostic threshold, and performing a designated correction on the machine in response to the frequency response exceeding the diagnostic threshold.

A compensation quantity acquisition device acquires vibration of the movement target in a second axis direction, orthogonal to the first axis direction when the movement target is moved in the first axis direction, acquires a positional frequency characteristic by performing Fourier transformation on the acquired vibration in the second axis direction, performs inverse Fourier transformation on the positional frequency characteristic from which the component of position independent frequency in the second axis direction (that occurs independently of a position of the movement target in the first axis direction) has been removed, to recover the vibration of the movement target in the second axial direction as position dependent vibration, and acquires positional compensation quantity of the movement target in the second axis direction that cancels the position dependent vibration.

A method for automated condition monitoring whereby techniques of automated vibration analysis and signal processing are combined with deep learning/machine learning techniques for an enhanced system of automated anomaly detection, problem classification, and problem regression. The method may be implemented in software, firmware or hardware to run autonomously. Machines monitored and analyzed according to the disclosed method are typically found in industrial plants or commercial applications, but the disclosed invention may be applied to any rotating equipment such as motors, fans, pumps, compressors, and etc., in any environment where they are functioning.

The present disclosure relates to an apparatus and a method for active vibration control of a hybrid electric vehicle. Exemplary forms provide a method for active vibration control of a hybrid electric vehicle that may include detecting an engine speed or a motor speed; selecting a reference angle signal based on position information of a motor or an engine; establishing a period of fast Fourier transform (FFT) and performing FFT of the engine speed or the motor speed corresponding to the period of the FFT from the reference angle signal; establishing a reference spectrum according to an engine speed and an engine load; extracting a vibration components to be removed based on information of the reference spectrum; summing vibration components to be removed according to the frequencies and performing inverse FFT; determining an amplitude ratio according to the engine speed and the engine load; determining an adjustable rate such that a speed change amount of the engine is increased as an anti-phase torque is increased; and performing active vibration control of each frequency based on the information of the basic amplitude ratio, the adjustable rate, and the engine torque.